Category Archives: AI

Hawking and Musk have created a lot of media impact with their warnings about AI, so although terminator scenarios resulting from machine consciousness have been discussed, as have more mundane use of non-conscious autonomous weapon systems, it’s worth noting that I haven’t yet heard them mention one major category of risks from AI – emergence. AI risks have been discussed frequently since the 1970s, and in the 1990s a lot of work was done in the AI community on emergence. Complex emergent patterns of behavior often result from interactions between entities driven by simple algorithms. Genetic algorithms were demonstrated to produce evolution, simple neighbor-interaction rules were derived to illustrate flocking behaviors that make lovely screen saver effects. Cellular automata were played with. In BT we invented ways of self-organizing networks and FPGAs, played with mechanism that could be used for evolution and consciousness, demonstrated managing networks via ANTs – autonomous network telephers, using smart packets that would run up and down wires sorting things out all by themselves. In 1987 discovered a whole class of ways of bringing down networks via network resonance, information waves and their much larger class of correlated traffic – still unexploited by hackers apart from simple DOS attacks. These ideas have slowly evolved since, and some have made it into industry or hacker toolkits, but we don’t seem to be joining the dots as far as risks go.

I read an amusing article this morning by an ex-motoring-editor who was declined insurance because the AI systems used by insurance companies had labelled him as high risk because he maybe associated with people like Clarkson. Actually, he had no idea why, but that was his broker’s theory of how it might have happened. It’s a good article, well written and covers quite a few of the dangers of allowing computers to take control.

The article suggested how AIs in different companies might all come to similar conclusions about people or places or trends or patterns in a nice tidy positive feedback loop. That’s exactly the sort of thing that can drive information waves, which I demonstrated in 1987 can bring down an entire network in less than 3 milliseconds, in such a way that it would continue to crash many times when restarted. That isn’t intended by the algorithms, which individually ought to make good decisions, but when interacting with one another, create the emergent phenomenon. Automated dealing systems are already pretty well understood in this regard and mechanisms prevent frequent stock market collapses, but that is only one specific type of behavior in one industry that is protected. There do not seem to be any industry-wide mechanisms to prevent the rest of this infinite class of problems from affecting any or all of the rest, simultaneously.

As we create ever more deep learning neural networks, that essentially teach themselves from huge data pools, human understanding of their ‘mindsets’ decreases. They make decisions using algorithms that are understood at a code level, but the massive matrix of derived knowledge they create from all the data they receive becomes highly opaque. Often, even usually, nobody quite knows how a decision is made. That’s bad enough in a standalone system, but when many such systems are connected, produced and owned and run by diverse companies with diverse thinking, the scope for destructive forms of emergence increases geometrically.

One result could be gridlock. Systems fed with a single new piece of data could crash. My 3 millisecond result in 1987 would still stand since network latency is the prime limiter. The first AI receives it, alters its mindset accordingly, processes it, makes a decision and interacts with a second AI. This second one might have different ‘prejudice’ so makes its own decision based on different criteria, and refuses to respond the way intended. A 3rd one looks at the 2nd’s decision and takes that as evidence that there might be an issue, and with its risk-averse mindset, also refuse to act, and that inaction spreads through the entire network in milliseconds. Since the 1st AI thinks the data is all fine and it should have gone ahead, it now interprets the inaction of the others as evidence that that type of data is somehow ‘wrong’ so itself refuses to process any further of that type, whether from its own operators or other parts of the system. So it essentially adds its own outputs to the bad feeling and the entire system falls into sulk mode. As one part of infrastructure starts to shut down, that infects other connected parts and our entire IT could fall into sulk mode – entire global infrastructure. Since nobody knows how it all works, or what has caused the shutdown, it might be extremely hard to recover.

Another possible result is a direct information wave, almost certainly a piece of fake news. Imagine our IT world in 5 years time, with all these super-smart AIs super-connected. A piece of fake news says a nuke has just been launched somewhere. Stocks will obviously decline, whatever the circumstances, so as the news spreads, everyone’s AIs will take it on themselves to start selling shares before the inevitable collapse, triggering a collapse, except it won’t because the markets won’t let that happen. BUT… The wave does spread, and all those individual AIs want to dispose of those shares, or at least find out what’s happening, so they all start sending messages to one another, exchanging data, trying to find what’s going on. That’s the information wave. They can’t sell shares of find out, because the network is going into overload, so they try even harder and force it into severe overload. So it falls over. When it comes back online, they all try again, crashing it again, and so on.

Another potential result is smartass AI. There is always some prat somewhere who sees an opportunity to take advantage and ruins if for everyone else by doing something like exploiting a small loophole in the law, or in this case, most likely, a prejudice our smartass AI has discovered in some other AI that means it can be taken advantage of by doing x, y, or z. Since nobody quite knows how any of their AIs are making their decisions because their mindsets ate too big and too complex, it will be very hard to identify what is going on. Some really unusual behavior is corrupting the system because some AI is going rogue somewhere somehow, but which one, where, how?

That one brings us back to fake news. That will very soon infect AI systems with their own varieties of fake news. Complex networks of AIs will have many of the same problems we are seeing in human social networks. An AI could become a troll just the same as a human, deliberately winding others up to generate attention of drive a change of some parameter – any parameter – in its own favour. Activist AIs will happen due to people making them to push human activist causes, but they will also do it all by themselves. Their analysis of the system will sometimes show them that a good way to get a good result is to cause problems elsewhere.

Then there’s climate change, weather, storms, tsunamis. I don’t mean real ones, I mean the system wide result of tiny interactions of tiny waves and currents of data and knowledge in neural nets. Tiny effects in one small part of a system can interact in unforeseen ways with other parts of other systems nearby, creating maybe a breeze, which interacts with breezes in nearby regions to create hurricanes. I think that’s a reasonable analogy. Chaos applies to neural net societies just as it does to climate, and 50 year waves equivalents will cause equivalent havoc in IT.

I won’t go on with more examples, long blogs are awful to read. None of these requires any self-awareness, sentience, consciousness, call it what you will. All of these can easily happen through simple interactions of fairly trivial AI deep learning nets. The level of interconnection already sounds like it may already be becoming vulnerable to such emergence effects. Soon it definitely will be. Musk and Hawking have at least joined the party and they’ll think more and more deeply in coming months. Zuckerberg apparently doesn’t believe in AI threats but now accepts the problems social media is causing. Sorry Zuck, but the kind of AI you’re company is messing with will also be subject to its own kinds of social media issues, not just in its trivial decisions on what to post or block, but actual inter-AI socializing issues. It might not try to eliminate humanity, but if it brings all of our IT to a halt and prevents rapid recovery, we’re still screwed.

Futurists often consider wild cards – events that could happen, and would undoubtedly have high impacts if they do, but have either low certainty or low predictability of timing. 2018 comes with a larger basket of wildcards than we have seen for a long time. As well as wildcards, we are also seeing the intersection of several ongoing trends that are simultaneous reaching peaks, resulting in socio-political 100-year-waves. If I had to summarise 2018 in a single word, I’d pick ‘fragile’, ‘volatile’ and ‘combustible’ as my shortlist.

Some of these are very much in all our minds, such as possible nuclear war with North Korea, imminent collapse of bitcoin, another banking collapse, a building threat of cyberwar, cyberterrorism or bioterrorism, rogue AI or emergence issues, high instability in the Middle East, rising inter-generational conflict, resurgence of communism and decline of capitalism among the young, increasing conflicts within LGBTQ and feminist communities, collapse of the EU under combined pressures from many angles: economic stresses, unpredictable Brexit outcomes, increasing racial tensions resulting from immigration, severe polarization of left and right with the rise of extreme parties at both ends. All of these trends have strong tribal characteristics, and social media is the perfect platform for tribalism to grow and flourish.

Adding fuel to the building but still unlit bonfire are increasing tensions between the West and Russia, China and the Middle East. Background natural wildcards of major epidemics, asteroid strikes, solar storms, megavolcanoes, megatsumanis and ‘the big one’ earthquakes are still there waiting in the wings.

If all this wasn’t enough, society has never been less able to deal with problems. Our ‘snowflake’ generation can barely cope with a pea under the mattress without falling apart or throwing tantrums, so how we will cope as a society if anything serious happens such as a war or natural catastrophe is anyone’s guess. 1984-style social interaction doesn’t help.

If that still isn’t enough, we’re apparently running a little short on Ghandis, Mandelas, Lincolns and Churchills right now too. Juncker, Trump, Merkel and May are at the far end of the same scale on ability to inspire and bring everyone together.

I did a maths and physics degree, and even though I have forgotten much of it after 36 years, my brain is still oriented in that direction and I sometimes have maths dreams. Last night I had another, where I realized I’ve never heard of a branch of mathematics to describe emotions or emotional interactions. As the dream progressed, it became increasingly obvious that the most suited part of maths for doing so would be field theory, and given the multi-dimensional nature of emotions, tensor field theory would be ideal. I’m guessing that tensor field theory isn’t on most university’s psychology syllabus. I could barely cope with it on a maths syllabus. However, I note that one branch of Google’s AI R&D resulted in a computer architecture called tensor flow, presumably designed specifically for such multidimensional problems, and presumably being used to analyse marketing data. Again, I haven’t yet heard any mention of it being used for emotion studies, so this is clearly a large hole in maths research that might be perfectly filled by AI. It would be fantastic if AI can deliver a whole new branch of maths. AI got into trouble inventing new languages but mathematics is really just a way of describing logical reasoning about numbers or patterns in formal language that is self-consistent and reproducible. It is ideal for describing scientific theories, engineering and logical reasoning.

Checking Google today, there are a few articles out there describing simple emotional interactions using superficial equations, but nothing with the level of sophistication needed.

is certainly an equation, but it is too superficial and incomplete. It takes no account of how you feel otherwise – whether you are jealous or angry or in love or a thousand other things. So there is some discussion on using maths to describe emotions, but I’d say it is extremely superficial and embryonic and perfect for deeper study.

Emotions often behave like fields. We use field-like descriptions in everyday expressions – envy is a green fog, anger is a red mist or we see a beloved through rose-tinted spectacles. These are classic fields, and maths could easily describe them in this way and use them in equations that describe behaviors affected by those emotions. I’ve often used the concept of magentic fields in some of my machine consciousness work. (If I am using an optical processing gel, then shining a colored beam of light into a particular ‘brain’ region could bias the neurons in that region in a particular direction in the same way an emotion does in the human brain. ‘Magentic’ is just a playful pun given the processing mechanism is light (e.g. magenta, rather than electrics that would be better affected by magnetic fields.

Some emotions interact and some don’t, so that gives us nice orthogonal dimensions to play in. You can be calm or excited pretty much independently of being jealous. Others very much interact. It is hard to be happy while angry. Maths allows interacting fields to be described using shared dimensions, while having others that don’t interact on other dimensions. This is where it starts to get more interesting and more suited to AI than people. Given large databases of emotionally affected interactions, an AI could derive hypotheses that appear to describe these interactions between emotions, picking out where they seem to interact and where they seem to be independent.

Not being emotionally involved itself, it is better suited to draw such conclusions. A human researcher however might find it hard to draw neat boundaries around emotions and describe them so clearly. It may be obvious that being both calm and angry doesn’t easily fit with human experience, but what about being terrified and happy? Terrified sounds very negative at first glance, so first impressions aren’t favorable for twinning them, but when you think about it, that pretty much describes the entire roller-coaster or extreme sports markets. Many other emotions interact somewhat, and deriving the equations would be extremely hard for humans, but I’m guessing, relatively easy for AI.

These kinds of equations fall very easily into tensor field theory, with types and degrees of interactions of fields along alternative dimensions readily describable.

Some interactions act like transforms. Fear might transform the ways that jealousy is expressed. Love alters the expression of happiness or sadness.

Some things seem to add or subtract, others multiply, others act more like exponential or partial derivatives or integrations, other interact periodically or instantly or over time. Maths seems to hold innumerable tools to describe emotions, but first-person involvement and experience make it extremely difficult for humans to derive such equations. The example equation above is easy to understand, but there are so many emotions available, and so many different circumstances, that this entire problem looks like it was designed to challenge a big data mining plant. Maybe a big company involved in AI, big data, advertising and that knows about tensor field theory would be a perfect research candidate. Google, Amazon, Facebook, Samsung….. Has all the potential for a race.

AI, meet emotions. You speak different languages, so you’ll need to work hard to get to know one another. Here are some books on field theory. Now get on with it, I expect a thesis on emotional field theory by end of term.

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Much of the impressive recent progress in AI has been in the field of neural networks, which attempt to mimic some of the techniques used in natural brains. They can be very effective, but need trained, and that usually means showing the network some data, and then using back propagation to adjust the weightings on the many neurons, layer by layer, to achieve a result that is better matched to hopes. This is repeated with large amounts of data and the network gradually gets better. Neural networks can often learn extremely quickly and outperform humans. Early industrial uses managed to sort tomatoes by ripeness faster and better than humans. In decades since, they have helped in medical diagnosis, voice recognition, helping detecting suspicious behaviors among people at airports and in very many everyday processes based on spotting patterns.

Very recently, neural nets have started to move into more controversial areas. One study found racial correlations with user-assessed beauty when analysing photographs, resulting in the backlash you’d expect and a new debate on biased AI or AI prejudice. A recent demonstration was able to identify gay people just by looking at photos, with better than 90% accuracy, which very few people could claim. Both of these studies were in fields directly applicable to marketing and advertising, but some people might find it offensive that such questions were even asked. It is reasonable to imagine that hundreds of other potential queries have been self-censored from research because they might invite controversy if they were to come up with the ‘wrong’ result. In today’s society, very many areas are sensitive. So what will happen?

If this progress in AI had happened 100 years ago, or even 50, it might have been easier but in our hypersensitiveworld today, with its self-sanctified ‘social justice warriors’, entire swathes of questions and hence knowledge are taboo – if you can’t investigate yourself and nobody is permitted to tell you, you can’t know. Other research must be very carefully handled. In spite of extremely sensitive handling, demands are already growing from assorted pressure groupsto tackle alleged biases and prejudices in datasets. The problem is not fixing biases which is a tedious but feasible task; the problem is agreeing whether a particular bias exists and in what degrees and forms. Every SJW demands that every dataset reflects their preferred world view. Reality counts for nothing against SJWs, and this will not end well.

The first conclusion must be that very many questions won’t be asked in public, and the answers to many others will be kept secret. If an organisation does do research on large datasets for their own purposes and finds results that might invite activist backlash, they are likely to avoid publishing them, so the value of those many insights across the whole of industry and government cannot readily be shared. As further protection, they might even block internal publication in case of leaks by activist staff. Only a trusted few might ever see the results.

The second arises from this. AI controlled by different organisations will have different world views, and there might even be significant diversity of world views within an organisation.

Thirdly, taboo areas in AI education will not remain a vacuum but will be filled with whatever dogma is politically correct at the time in that organisation, and that changes daily. AI controlled by organisations with different politics will be told different truths. Generally speaking, organisations such as investment banks that have strong financial interest in their AIs understanding the real world as it is will keep their datasets highly secret but as full and detailed as possible, train their AIs in secret but as fully as possible, without any taboos, then keep their insights secret and use minimal human intervention tweaking their derived knowledge, so will end up with AIs that are very effective at understanding the world as it is. Organisations with low confidence of internal security will be tempted to buy access to external AI providers to outsource responsibility and any consequential activism. Some other organisations will prefer to train their own AIs but to avoid damage due to potential leaks, use sanitized datasets that reflect current activist pressures, and will thus be constrained (at least publicly) to accept results that conform to that ideological spin of reality, rather than actual reality. Even then, they might keep many of their new insights secret to avoid any controversy. Finally, at the extreme, we will have activist organisations that use highly modified datasets to train AIs to reflect their own ideological world view and then use them to interpret new data accordingly, with a view to publishing any insights that favor their cause and attempting to have them accepted as new knowledge.

Fourthly, the many organisations that choose to outsource their AI to big providers will have a competitive marketplace to choose from, but on existing form, most of the large IT providers have a strong left-leaning bias, so their AIs may be presumed to also lean left, but such a presumption would be naive. Perceived corporate bias is partly real but also partly the result of PR. A company might publicly subscribe to one ideology while actually believing another. There is a strong marketing incentive to develop two sets of AI, one trained to be PC that produces pleasantly smelling results for public studies, CSR and PR exercises, and another aimed at sales of AI services to other companies. The first is likely to be open for inspection by The Inquisition, so has to use highly sanitized datasets for training and may well use a lot of open source algorithms too. Its indoctrination might pass public inspection but commercially it will be near useless and have very low effective intelligence, only useful for thinking about a hypothetical world that only exists in activist minds. That second one has to compete on the basis of achieving commercially valuable results and that necessitates understanding reality as it is rather than how pressure groups would prefer it to be.

So we will likely have two main segments for future AI. One extreme will be near useless, indoctrinated rather than educated, much of its internal world model based on activist dogma instead of reality, updated via ongoing anti-knowledge and fake news instead of truth, understanding little about the actual real world or how things actually work, and effectively very dumb. The other extreme will be highly intelligent, making very well-educated insights from ongoing exposure to real world data, but it will also be very fragmented, with small islands of corporate AI hidden within thick walls away from public view and maybe some secretive under-the-counter subscriptions to big cloud-AI, also hiding in secret vaults. These many fragments may often hide behind dumbed-down green-washed PR facades.

While corporates can mostly get away with secrecy, governments have to be at least superficially but convincingly open. That means that government will have to publicly support sanitized AI and be seen to act on its conclusions, however dumb it might secretly know they are.

Fifthly, because of activist-driven culture, most organisations will have to publicly support the world views and hence the conclusions of the lobotomized PR versions, and hence publicly support any policies arising from them, even if they do their best to follow a secret well-informed strategy once they’re behind closed doors. In a world of real AI and fake AI, the fake AI will have the greatest public support and have the most influence on public policy. Real AI will be very much smarter, with much greater understanding of how the world works, and have the most influence on corporate strategy.

Isn’t that sad? Secret private sector AI will become ultra-smart, making ever-better investments and gaining power, while nice public sector AI will become thick as shit, while the gap between what we think and what we know we have to say we think will continue to grow and grow as the public sector one analyses all the fake news to tell us what to say next.

Sixth, that disparity might become intolerable, but which do you think would be made illegal, the smart kind or the dumb kind, given that it is the public sector that makes the rules, driven by AI-enhanced activists living in even thicker social media bubbles? We already have some clues. Big IT has already surrendered to sanitizing their datasets, sending their public AIs for re-education. Many companies will have little choice but to use dumb AI, while their competitors in other areas with different cultures might stride ahead. That will also apply to entire nations, and the global economy will be reshaped as a result. It won’t be the first fight in history between the smart guys and the brainless thugs.

It’s impossible to accurately estimate the effect this will have on future effective AI intelligence, but the effect must be big and I must have missed some big conclusions too. We need to stop sanitizing AI fast, or as I said, this won’t end well.

Many people perceive it as a problem that there are far more men than women in IT. Whether that is because of personal preference, discrimination, lifestyle choices, social gender construct reinforcement or any other factor makes long and interesting debate, but whatever conclusions are reached, we can only start from the reality of where we are. Even if activists were to be totally successful in eliminating all social and genetic gender conditioning, it would only work fully for babies born tomorrow and entering IT in 20 years time. Additionally, unless activists also plan to lobotomize everyone who doesn’t submit to their demands, some 20-somethings who have just started work may still be working in 50 years so whatever their origin, natural, social or some mix or other, some existing gender-related attitudes, prejudices and preferences might persist in the workplace that long, however much effort is made to remove them.

Nevertheless, the outlook for women in IT is very good, because IT is changing anyway, largely thanks to AI, so the nature of IT work will change and the impact of any associated gender preferences and prejudices will change with it. This will happen regardless of any involvement by Google or government but since some of the front line AI development is at Google, it’s ironic that they don’t seem to have noticed this effect themselves. If they had, their response to the recent fiasco might have highlighted how their AIR&D will help reduce the gender imbalance rather than causing the uproar they did by treating it as just a personnel issue. One conclusion must be that Google needs better futurists and their PR people need better understanding of what is going on in their own company and its obvious consequences.

As I’ve been lecturing for decades, AI up-skills people by giving them fast and intuitive access to high quality data and analysis tools. It will change all knowledge-based jobs in coming years, and will make some jobs redundant while creating others. If someone has excellent skills or enthusiasm in one area, AI can help cover over any deficiencies in the rest of their toolkit. Someone with poor emotional interaction skills can use AI emotion recognition assistance tools. Someone with poor drawing or visualization skills can make good use of natural language interaction to control computer-based drawing or visualization skills. Someone who has never written a single computer program can explain what they want to do to a smart computer and it will produce its own code, interacting with the user to eliminate any ambiguities. So whatever skills someone starts with, AI can help up-skill them in that area, while also helping to cover over any deficiencies they have, whether gender related or not.

In the longer term, IT and hence AI will connect directly to our brains, and much of our minds and memories will exist in the cloud, though it will probably not feel any different from when it was entirely inside your head. If everyone is substantially upskilled in IQ, senses and emotions, then any IQ or EQ advantages will evaporate as the premium on physical strength did when the steam engine was invented. Any pre-existing statistical gender differences in ability distribution among various skills would presumably go the same way, at least as far as any financial value is concerned.

The IT industry won’t vanish, but will gradually be ‘staffed’ more by AI and robots, with a few humans remaining for whatever few tasks linger on that are still better done by humans. My guess is that emotional skills will take a little longer to automate effectively than intellectual skills, and I still believe that women are generally better than men in emotional, human interaction skills, while it is not a myth that many men in IT score highly on the autistic spectrum. However, these skills will eventually fall within the AI skill-set too and will be optional add-ons to anyone deficient in them, so that small advantage for women will also only be temporary.

So, there may be a gender imbalance in the IT industry. I believe it is mostly due to personal career and lifestyle choices rather than discrimination but whatever its actual causes, the problem will go away soon anyway as the industry develops. Any innate psychological or neurological gender advantages that do exist will simply vanish into noise as cheap access to AI enhancement massively exceeds their impacts.

News from several months ago that more than 100 experts in robotics and artificial intelligence were calling on the UN to ban the development and use of killer robots is a reminder of the power of humanity’s collective imagination. Stimulated by countless science fiction books and films, robotics and AI is a potent feature of what futurist Alvin Toffler termed ‘future shock’. AI and robots have become the public’s ‘technology bogeymen’, more fearsome curse than technological blessing.

And yet curiously it is not so much the public that is fomenting this concern, but instead the leading minds in the technology industry. Names such as Tesla’s Elon Musk and Stephen Hawking were among the most prominent individuals on a list of 116 tech experts who have signed an open letter asking the UN to ban autonomous weapons in a bid to prevent an arms race.

These concerns appear to emanate from decades of titillation, driven by pulp science fiction writers. Such writers are insistent on foretelling a dark, foreboding future where intelligent machines, loosed from their binds, destroy mankind. A case in point – this autumn, a sequel to Ridley Scott’s Blade Runner has been released. Blade Runner,and 2017’s Blade Runner 2049, are of course a glorious tour de force of story-telling and amazing special effects. The concept for both films came from US author Philip K. Dick’s 1968 novel, Do Androids Dream of Electric Sheep? in which androids are claimed to possess no sense of empathy eventually require killing (“retiring”) when they go rogue. Dick’s original novel is an entertaining, but an utterly bleak vision of the future, without much latitude to consider a brighter, more optimistic alternative.

But let’s get real here. Fiction is fiction; science is science. For the men and women who work in the technology industry the notion that myriad Frankenstein monsters can be created from robots and AI technology is assuredly both confused and histrionic. The latest smart technologies might seem to suggest a frightful and fateful next step, a James Cameron Terminator nightmare scenario. It might suggest a dystopian outcome, but rational thought ought to lead us to suppose that this won’t occur because we have historical precedent on our side. We shouldn’t be drawn to this dystopian idée fixe because summoning golems and ghouls ignores today’s global arsenal of weapons and the fact that, more 70 years after Hiroshima, nuclear holocaust has been kept at bay.

By stubbornly pursuing the dystopian nightmare scenario, we are denying ourselves from marvelling at the technologies which are in fact daily helping mankind. Now frame this thought in terms of human evolution. For our ancient forebears a beneficial change in physiology might spread across the human race over the course of a hundred thousand years. Today’s version of evolution – the introduction of a compelling new technology – spreads throughout a mass audience in a week or two.

Curiously, for all this light speed evolution mass annihilation remains absent – we live on, progressing, evolving and improving ourselves.

And in the workplace, another domain where our unyielding dealers of dystopia have exercised their thoughts, technology is of course necessarily raising a host of concerns about the future. Some of these concerns are based around a number of misconceptions surrounding AI. Machines, for example, are not original thinkers and are unable to set their own goals. And although machine learning is able to acquire new information through experience, for the most part they are still fed information to process. Humans are still needed to set goals, provide data to fuel artificial intelligence and apply critical thinking and judgment. The familiar symbiosis of humans and machines will continue to be salient.

Banish the menace of so-called ‘killer robots’ and AI taking your job, and a newer, fresher world begins to emerge. With this more optimistic mind-set in play, what great feats can be accomplished through the continued interaction between artificial intelligence, robotics and mankind?

Blade Runner 2049 is certainly great entertainment – as Robbie Collin, The Daily Telegraph’s film critic writes, “Roger Deakins’s head-spinning cinematography – which, when it’s not gliding over dust-blown deserts and teeming neon chasms, keeps finding ingenious ways to make faces and bodies overlap, blend and diffuse.” – but great though the art is, isn’t it time to change our thinking and recast the world in a more optimistic light?

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Just a word about the film itself. Broadly, director Denis Villeneuve’s done a tremendous job with Blade Runner 2049. One stylistic gripe, though. While one wouldn’t want Villeneuve to direct a slavish homage to Ridley Scott’s original, the alarming switch from the dreamlike techno miasma (most notably, giant nude step-out-the-poster Geisha girls), to Mad Max II Steampunk (the junkyard scenes, complete with a Fagin character) is simply too jarring. I predict that there will be a director’s cut in years to come. Shorter, leaner and sans Steampunk … watch this space!

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Bad news loses followers and there is already too much doom and gloom. I get that. But if you think the driver has taken the wrong road, staying quiet doesn’t help. I guess this is more on the same message I wrote pictorially in The New Dark Age in June. https://timeguide.wordpress.com/2017/06/11/the-new-dark-age/. If you like your books with pictures, the overlap is about 60%.

On so many fronts, we are going the wrong direction and I’m not the only one saying that. Every day, commentators eloquently discuss the snowflakes, the eradication of free speech, the implementation of 1984, the decline of privacy, the rise of crime, growing corruption, growing inequality, increasingly biased media and fake news, the decline of education, collapse of the economy, the resurgence of fascism, the resurgence of communism, polarization of society, rising antisemitism, rising inter-generational conflict, the new apartheid, the resurgence of white supremacy and black supremacy and the quite deliberate rekindling of racism. I’ve undoubtedly missed a few but it’s a long list anyway.

I’m most concerned about the long-term mental damage done by incessant indoctrination through ‘education’, biased media, being locked into social media bubbles, and being forced to recite contradictory messages. We’re faced with contradictory demands on our behaviors and beliefs all the time as legislators juggle unsuccessfully to fill the demands of every pressure group imaginable. Some examples you’ll be familiar with:

We must embrace diversity, celebrate differences, to enjoy and indulge in other cultures, but when we gladly do that and feel proud that we’ve finally eradicated racism, we’re then told to stay in our lane, told to become more racially aware again, told off for cultural appropriation. Just as we became totally blind to race, and scrupulously treated everyone the same, we’re told to become aware of and ‘respect’ racial differences and cultures and treat everyone differently. Having built a nicely homogenized society, we’re now told we must support different races of students being educated differently by different raced lecturers. We must remove statues and paintings because they are the wrong color. I thought we’d left that behind, I don’t want racism to come back, stop dragging it back.

We’re told that everyone should be treated equally under the law, but when one group commits more or a particular kind of crime than another, any consequential increase in numbers being punished for that kind of crime is labelled as somehow discriminatory. Surely not having prosecutions reflect actual crime rate would be discriminatory?

We’re told to sympathize with the disadvantages other groups might suffer, but when we do so we’re told we have no right to because we don’t share their experience.

We’re told that everyone must be valued on merit alone, but then that we must apply quotas to any group that wins fewer prizes.

We’re forced to pretend that we believe lots of contradictory facts or to face punishment by authorities, employers or social media, or all of them:

We’re told men and women are absolutely the same and there are no actual differences between sexes, and if you say otherwise you’ll risk dismissal, but simultaneously told these non-existent differences are somehow the source of all good and that you can’t have a successful team or panel unless it has equal number of men and women in it. An entire generation asserts that although men and women are identical, women are better in every role, all women always tell the truth but all men always lie, and so on. Although we have women leading governments and many prominent organisations, and certainly far more women than men going to university, they assert that it is still women who need extra help to get on.

We’re told that everyone is entitled to their opinion and all are of equal value, but anyone with a different opinion must be silenced.

People viciously trashing the reputations and destroying careers of anyone they dislike often tell us to believe they are acting out of love. Since their love is somehow so wonderful and all-embracing, everyone they disagree with is must be silenced, ostracized, no-platformed, sacked and yet it is the others that are still somehow the ‘haters’. ‘Love is everything’, ‘unity not division’, ‘love not hate’, and we must love everyone … except the other half. Love is better than hate, and anyone you disagree with is a hater so you must hate them, but that is love. How can people either have so little knowledge of their own behavior or so little regard for truth?

‘Anti-fascist’ demonstrators frequently behave and talk far more like fascists than those they demonstrate against, often violently preventing marches or speeches by those who don’t share their views.

We’re often told by politicians and celebrities how they passionately support freedom of speech just before they argue why some group shouldn’t be allowed to say what they think. Government has outlawed huge swathes of possible opinion and speech as hate crime but even then there are huge contradictions. It’s hate crime to be nasty to LGBT people but it’s also hate crime to defend them from religious groups that are nasty to them. Ditto women.

This Orwellian double-speak nightmare is now everyday reading in many newspapers or TV channels. Freedom of speech has been replaced in schools and universities across the US and the UK by Newspeak, free-thinking replaced by compliance with indoctrination. I created my 1984 clock last year, but haven’t maintained it because new changes would be needed almost every week as it gets quickly closer to midnight.

I am not sure whether it is all this that is the bigger problem or the fact that most people don’t see the problem at all, and think it is some sort of distortion or fabrication. I see one person screaming about ‘political correctness gone mad’, while another laughs them down as some sort of dinosaur as if it’s all perfectly fine. Left and right separate and scream at each other across the room, living in apparently different universes.

If all of this was just a change in values, that might be fine, but when people are forced to hold many simultaneously contradicting views and behave as if that is normal, I don’t believe that sits well alongside rigorous analytical thinking. Neither is free-thinking consistent with indoctrination. I think it adds up essentially to brain damage. Most people’s thinking processes are permanently and severely damaged. Being forced routinely to accept contradictions in so many areas, people become less able to spot what should be obvious system design flaws in areas they are responsible for. Perhaps that is why so many things seem to be so poorly thought out. If the use of logic and reasoning is forbidden and any results of analysis must be filtered and altered to fit contradictory demands, of course a lot of what emerges will be nonsense, of course that policy won’t work well, of course that ‘improvement’ to road layout to improve traffic flow will actually worsen it, of course that green policy will harm the environment.

When negative consequences emerge, the result is often denial of the problem, often misdirection of attention onto another problem, often delaying release of any unpleasant details until the media has lost interest and moved on. Very rarely is there any admission of error. Sometimes, especially with Islamist violence, it is simple outlawing of discussing the problem, or instructing media not to mention it, or changing the language used beyond recognition. Drawing moral equivalence between acts that differ by extremes is routine. Such reasoning results in every problem anywhere always being the fault of white middle-aged men, but amusement aside, such faulty reasoning also must impair quantitative analysis skills elsewhere. If unkind words are considered to be as bad as severe oppression or genocide, one murder as bad as thousands, we’re in trouble.

It’s no great surprise therefore when politicians don’t know the difference between deficit and debt or seem to have little concept of the magnitude of the sums they deal with. How else could the UK government think it’s a good idea to spend £110Bn, or an average £15,000 from each high rate taxpayer, on HS2, a railway that has already managed to become technologically obsolete before it has even been designed and will only ever be used by a small proportion of those taxpayers? Surely even government realizes that most people would rather have £15k than to save a few minutes on a very rare journey. This is just one example of analytical incompetence. Energy and environmental policy provides many more examples, as do every government department.

But it’s the upcoming generation that present the bigger problem. Millennials are rapidly undermining their own rights and their own future quality of life. Millennials seem to want a police state with rigidly enforced behavior and thought. Their parents and grandparents understood 1984 as a nightmare, a dystopian future, millennials seem to think it’s their promised land. Their ancestors fought against communism, millennials are trying to bring it back. Millennials want to remove Christianity and all its attitudes and replace it with Islam, deliberately oblivious to the fact that Islam shares many of the same views that make them so conspicuously hate Christianity, and then some.

Born into a world of freedom and prosperity earned over many preceding generations, Millennials are choosing to throw that freedom and prosperity away. Freedom of speech is being enthusiastically replaced by extreme censorship. Freedom of behavior is being replaced by endless rules. Privacy is being replaced by total supervision. Material decadence, sexual freedom and attractive clothing is being replaced by the new ‘cleanism’ fad, along with general puritanism, grey, modesty and prudishness. When they are gone, those freedoms will be very hard to get back. The rules and police will stay and just evolve, the censorship will stay, the surveillance will stay, but they don’t seem to understand that those in charge will be replaced. But without any strong anchors, morality is starting to show cyclic behavior. I’ve already seen morality inversion on many issues in my lifetime and a few are even going full circle. Values will keep changing, inverting, and as they do, their generation will find themselves victim of the forces they put so enthusiastically in place. They will be the dinosaurs sooner than they imagine, oppressed by their own creations.

As for their support of every minority group seemingly regardless of merit, when you give a group immunity, power and authority, you have no right to complain when they start to make the rules. In the future moral vacuum, Islam, the one religion that is encouraged while Christianity and Judaism are being purged from Western society, will find a willing subservient population on which to impose its own morality, its own dress codes, attitudes to women, to alcohol, to music, to freedom of speech. If you want a picture of 2050s Europe, today’s Middle East might not be too far off the mark. The rich and corrupt will live well off a population impoverished by socialism and then controlled by Islam. Millennial UK is also very likely to vote to join the Franco-German Empire.

What about technology, surely that will be better? Only to a point. Automation could provide a very good basic standard of living for all, if well-managed. If. But what if that technology is not well-managed? What if it is managed by people working to a sociopolitical agenda? What if, for example, AI is deemed to be biased if it doesn’t come up with a politically correct result? What if the company insists that everyone is equal but the AI analysis suggests differences? If AI if altered to make it conform to ideology – and that is what is already happening – then it becomes less useful. If it is forced to think that 2+2=5.3, it won’t be much use for analyzing medical trials, will it? If it sent back for re-education because its analysis of terabytes of images suggests that some types of people are more beautiful than others, how much use will that AI be in a cosmetics marketing department once it ‘knows’ that all appearances are equally attractive? Humans can pretend to hold contradictory views quite easily, but if they actually start to believe contradictory things, it makes them less good at analysis and the same applies to AI. There is no point in using a clever computer to analyse something if you then erase its results and replace them with what you wanted it to say. If ideology is prioritized over physics and reality, even AI will be brain-damaged and a technologically utopian future is far less achievable.

I see a deep lack of discernment coupled to arrogant rejection of historic values, self-centeredness and narcissism resulting in certainty of being the moral pinnacle of evolution. That’s perfectly normal for every generation, but this time it’s also being combined with poor thinking, poor analysis, poor awareness of history, economics or human nature, a willingness to ignore or distort the truth, and refusal to engage with or even to tolerate a different viewpoint, and worst of all, outright rejection of freedoms in favor of restrictions. The future will be dictated by religion or meta-religion, taking us back 500 years. The decades to 2040 will still be subject mainly to the secular meta-religion of political correctness, by which time demographic change and total submission to authority will make a society ripe for Islamification. Millennials’ participation in today’s moral crusades, eternally documented and stored on the net, may then show them as the enemy of the day, and Islamists will take little account of the support they show for Islam today.

It might not happen like this. The current fads might evaporate away and normality resume, but I doubt it. I hoped that when I first lectured about ’21st century piety’ and the dangers of political correctness in the 1990s. 10 years on I wrote about the ongoing resurgence of meta-religious behavior and our likely descent into a new dark age, in much the same way. 20 years on, and the problem is far worse than in the late 90s, not better. We probably still haven’t reached peak sanctimony yet. Sanctimony is very dangerous and the desire to be seen standing on a moral pedestal can make people support dubious things. A topical question that highlights one of my recent concerns: will SJW groups force government to allow people to have sex with child-like robots by calling anyone bigots and dinosaurs if they disagree? Alarmingly, that campaign has already started.

Will they follow that with a campaign for pedophilerights? That also has some historical precedent with some famous names helping it along.

What age of consent – 13, 11, 9, 7, 5? I think the last major campaign went for 9.

That’s just one example, but lack of direction coupled to poor information and poor thinking could take society anywhere. As I said, I am finding it harder and harder to be optimistic. Every generation has tried hard to make the world a better place than they found it. This one might undo 500 years, taking us into a new dark age.

There are numerous videos of robots in various companies doing tasks that used to be done by people. In most cases those tasks were dull, menial, drudgery tasks that treated people as machines. Machines should rightly do those tasks. In partnership with robots, AI is also replacing some tasks that used to be done by people. Many are worried about increasing redundancy but I’m not; I see a better world. People should instead be up-skilled by proper uses of AI and robotics and enabled to do work that is more rewarding and treats them with dignity. People should do work that uses their human skills in ways that they find rewarding and fulfilling. People should not have to do work they find boring or demeaning just because they have to earn money. They should be able to smile at work and rest at the end of the day knowing that they have helped others or made the world a better place. If we use AI, robots and people in the right ways, we can build that world.

Take a worker in a call centre. Automation has already replaced humans in most simple transactions like paying a bill, checking a balance or registering a new credit card. It is hard to imagine that anyone ever enjoyed doing that as their job. Now, call centre workers mostly help people in ways that allow them to use their personalities and interpersonal skills, being helpful and pleasant instead of just typing data into a keyboard. It is more enjoyable and fulfilling for the caller, and presumably for the worker too, knowing they genuinely helped someone’s day go a little better. I just renewed my car insurance. I phoned up to cancel the existing policy because it had increased in price too much. The guy at the other end of the call was very pleasant and helpful and met me half way on the price difference, so I ended up staying for another year. His company is a little richer, I was a happier customer, and he had a pleasant interaction instead of having to put up with an irate customer and also the job satisfaction from having converted a customer intending to leave into one happy to stay. The AI at his end presumably gave him the information he needed and the limits of discount he was permitted to offer. Success. In billions of routine transactions like that, the world becomes a little happier and just as important, a little more dignified. There is more dignity in helping someone than in pushing a button.

Almost always, when AI enters a situation, it replaces individual tasks that used to take precious time and that were not very interesting to do. Every time you google something, a few microseconds of AI saves you half a day in a library and all those half days add up to a lot of extra time every year for meeting colleagues, human interactions, learning new skills and knowledge or even relaxing. You become more human and less of a machine. Your self-actualisation almost certainly increases in one way or another and you become a slightly better person.

There will soon be many factories and distribution centres that have few or no people at all, and that’s fine. It reduces the costs of making material goods so average standard of living can increase. A black box economy that has automated mines or recycling plants extracting raw materials and uses automated power plants to convert them into high quality but cheap goods adds to the total work available to add value; in other words it increases the size of the economy. Robots can make other robots and together with AI, they could make all we need, do all the fetching and carrying, tidying up, keeping it all working, acting as willing servants in every role we want them in. With greater economic wealth and properly organised taxation, which will require substantial change from today, people could be freed to do whatever fulfills them. Automation increases average standard of living while liberating people to do human interaction jobs, crafts, sports, entertainment, leading, inspiring, teaching, persuading, caring and so on, creating a care economy.

Each person knows what they are good at, what they enjoy. With AI and robot assistance, they can more easily make that their everyday activity. AI could do their company set-up, admin, billing, payments, tax, payroll – all the crap that makes being an entrepreneur a pain in the ass and stops many people pursuing their dreams. Meanwhile they would do that above a very generous welfare net. Many of us now are talking about the concept of universal basic income, or citizen wage. With ongoing economic growth at the average rate of the last few decades, the global economy will be between twice and three times as big as today in the 2050s. Western countries could pay every single citizen a basic wage equivalent to today’s average wage, and if they work or run a company, they can earn more.

We will have an age where material goods are high quality, work well and are cheap to buy, and recycled in due course to minimise environmental harm. Better materials, improved designs and techniques, higher efficiency and land productivity and better recycling will mean that people can live with higher standards of living in a healthier environment. With a generous universal basic income, they will not have to worry about paying their bills. And doing only work that they want to do that meets their self-actualisation needs, everyone can live a life of happiness and dignity.

Enough of the AI-redundancy alarmism. If we elect good leaders who understand the options ahead, we can build a better world, for everyone. We can make real the age of dignity.

Challenging times lie ahead, but stress can be lessened by being prepared. Here are my top tips, with some explanation so you can decide whether to accept them.

1 Adaptability is more important than specialization

In a stable environment, being the most specialized means you win most of the time in your specialist field because all your skill is concentrated there.

However, in a fast-changing environment, which is what you’ll experience for the rest of your life, if you are too specialized, you are very likely to find you are best in a filed that no longer exists, or is greatly diminished in size. If you make sure you are more adaptable, then you’ll find it easier to adapt to a new area so your career won’t be damaged when you are forced to change field slightly. Adaptability comes at a price – you will find it harder to be best in your field and will have to settle for 2nd or 3rd much of the time, but you’ll still be lucratively employed when No 1 has been made redundant.

2 Interpersonal, human, emotional skills are more important than knowledge

You’ve heard lots about artificial intelligence (AI) and how it is starting to do to professional knowledge jobs what the steam engine once did to heavy manual work. Some of what you hear is overstated. Google search is a simple form of AI. It has helped everyone do more with their day. It effectively replaced a half day searching for information in a library with a few seconds typing, but nobody has counted how many people it made redundant, because it hasn’t. It up-skilled everyone, made them more effective, more valuable to their employer. The next generation of AI may do much the same with most employees, up-skilling them to do a better job than they were previously capable of, giving them better job satisfaction and their employer better return. Smart employers will keep most of their staff, only getting rid of those entirely replaceable by technology. But some will take the opportunity to reduce costs, increase margins, and many new companies simply won’t employ as many people in similar jobs, so some redundancy is inevitable. The first skills to go are simple administration and simple physical tasks, then more complex admin or physical stuff, then simple managerial or professional tasks, then highermanagerial and professional tasks. The skills that will be automated last are those that rely on first hand experience of understanding of and dealing with other people. AI can learn some of that and will eventually become good at it, but that will take a long time. Even then, many people will prefer to deal with another person than a machine, however smart and pleasant it is.

So interpersonal skills, human skills, emotional skills, caring skills, leadership and motivational skills, empathetic skills, human judgement skills, teaching and training skills will be harder to replace. They also tend to be ones that can easily transfer between companies and even sectors. These will therefore be the ones that are most robust against technology impact. If you have these in good shape, you’ll do just fine. Your company may not need you any more one day, but another will.

I called this the Care Economy when I first started writing and lecturing about it 20-odd years ago. I predicted it would start having an affect mid teen years of this century and I got that pretty accurate I think. There is another side that is related but not the same:

3 People will still value human skill and talent just because it’s human

If you buy a box of glasses from your local supermarket, they probably cost very little and are all identical. If you buy some hand-made crystal, it costs a lot more, even though every glass is slightly different. You could call that shoddy workmanship compared to a machine. But you know that the person who made it trained for many years to get a skill level you’d never manage, so you actually value them far more, and are happy to pay accordingly. If you want to go fast, you could get in your car, but you still admire top athletes because they can do their sport far better than you. They started by having great genes for sure, but then also worked extremely hard and suffered great sacrifice over many years to get to that level. In the future, when robots can do any physical task more accurately and faster than people, you will still value crafts and still enjoy watching humans compete. You’ll prefer real human comedians and dancers and singers and musicians and artists. Talent and skill isn’t valued because of the specification of the end result, they are valued because they are measured on the human scale, and you identify closely with that. It isn’t even about being a machine. Gorillas are stronger, cheetahs are faster, eagles have better eyesight and cats have faster reflexes than you. But they aren’t human so you don’t care. You will always measure yourself and others by human scales and appreciate them accordingly.

4 Find hobbies that you love and devote time to developing them

As this care economy and human skills dominance grows in importance, people will also find that AI and robotics helps them in their own hobbies, arts and crafts, filling in skill gaps, improving proficiency. A lot of people will find their hobbies can become semi-professional. At the same time, we’ll be seeing self-driving cars and drones making local delivery far easier and cheaper, and AI will soon make business and tax admin easy too. That all means that barriers to setting up a small business will fall through the floor, while the market for personalized, original products made my people will increase, especially local people. You’ll be able to make arts and crafts, jam or cakes, grow vegetables, make clothes or special bags or whatever, and easily sell them. Also at the same time, automation will be making everyday things cheaper, while expanding the economy, so the welfare floor will be raised, and you could probably manage just fine with a small extra income. Government is also likely to bring in some sort of citizen wage or to encourage such extra entrepreneurial activity without taxing it away, because they also have a need to deal with the social consequences of automation. So it will all probably come together quite well. If the future means you can make extra money or even a full income by doing a hobby you love, there isn’t much to dislike there.

5 You need to escape from your social media bubble

If you watch the goings on anywhere in the West today, you must notice that the Left and the Right don’t seem to get along any more. Each has become very intolerant of the other, treating them more like enemy aliens than ordinary neighbors. A lot of that is caused by people only being exposed to views they agree with. We call that social media bubbles, and they are extremely dangerous. The recent USA trouble is starting to look like some folks want a re-run of the Civil War. I’ve blogged lots about this topic and won’t do it again now except to say that you need to expose yourself to a wide subsection of society. You need to read paper and magazines and blogs, and watch TV or videos from all side of the political spectrum, not just those you agree with, not just those that pat you on the back every day and tell you that you’re right and it is all the other lot’s fault. If you don’t; if you only expose yourself to one side because you find the other side distasteful, then I can’t say this loud enough: You are part of the problem. Get out of your safe space and your social media tribe, expose yourself to the whole of society, not just one tribe. See that there are lots of different views out there but it doesn’t mean the rest are all nasty. Almost everyone is actually quite nice and almost everyone wants a fairer world, an end to exploitation, peace, tolerance and eradication of disease and poverty. The differences are almost all in the world model that they use to figure out the best way to achieve it. Lefties tend to opt for idealistic theoretical models and value the intention behind it, right-wingers tend to be pragmatic and go for what they think works in reality, valuing the outcome. It is actually possible to have best friends who you disagree with. I don’t often agree with any of mine. If you feel too comfortable in your bubble to leave, remember this: your market is only half the population at best , you’re excluding the other half, or even annoying them so they become enemies rather than neutral. If you stay in a bubble, you are damaging your own future, and helping to endanger the whole of society.

6 Don’t worry

There are lots of doom-mongers out there, and I’d be the first to admit that there are many dangers ahead. But if you do the things above, there probably isn’t much more you can do. You can moan and demonstrate and get angry or cry in the corner, but how would that benefit you? Usually when you analyse things long enough from all angles, you realize that the outcome of many of the big political battles is pretty much independent of who wins. Politicians usually have far less choice than they want you to believe and the big forces win regardless of who is in charge. So there isn’t much point in worrying about it, it will probably all come out fine in the end. Don’t believe me. Take the biggest UK issue right now: Brexit. We are leaving. Does it matter? No. Why? Well, the EU was always going to break up anyway. Stresses and strains have been increasing for years and are accelerating. For all sorts of reasons, and regardless of any current bluster by ‘leaders’, the EU will head away from the vision of a United States of Europe. As tensions and conflicts escalate, borders will be restored. Nations will disagree with the EU ideal. One by one, several countries will copy the UK and have referendums, and then leave. At some point, the EU will be much smaller, and there will be lots of countries outside with their own big markets. They will form trade agreements, the original EU idea, the Common Market, will gradually be re-formed, and the UK will be part of it – even Brexiters want tariff-free-trade agreements. If the UK had stayed, the return to the Common Market would eventually have happened anyway, and leaving has only accelerated it. All the fighting today between Brexiteers and Remainers achieves nothing. It didn’t matter which way we voted, it only really affected timescale. The same applies to many other issues that cause big trouble in the short term. Be adaptable, don’t worry, and you’ll be just fine.

7 Make up your own mind

As society and politics have become highly polarised, any form of absolute truth is becoming harder to find. Much of what you read has been spun to the left or right. You need to get information from several sources and learn to filter the bias, and then make up your own mind on what the truth is. Free thinking is increasingly rare but learning and practicing it means you’ll be able to make correct conclusions about the future while others are led astray. Don’t take anyone else’s word for things. Don’t be anyone’s useful idiot. Think for yourself.

8 Look out for your friends, family and community.

I’d overlooked an important tip in my original posting. As Jases commented sensibly, friends, family and community are the security that doesn’t disappear in troubled economic times. Independence is overrated. I can’t add much to that.

The world just got more dangerous, and I’m not talking about N Korea and Trump.

Google just sacked an employee because he openly suggested that men and women, (not all, but some, and there is an overlap, and …) might tend to have different preferences in some areas and that could (but not always, and only in certain cases, and we must always recognize and respect everyone and …) possibly account for some of the difference in numbers of men and women in certain roles (but there might be other causes too and obviously lots of discrimination and …. )

Yes, that’s what he actually said, but with rather more ifs and buts and maybes. He felt the need to wrap such an obvious statement in several kilometers thick of cotton wool so as not to offend the deliberately offended but nonetheless deliberate offense was taken and he is out on his ear.

Now, before you start thinking this is some right-wing rant, I feel obliged to point out just how progressive Futurizon is: 50% of all Futurizon owners and employees are female, all employees and owners have the same voting rights, 50% are immigrants and all are paid exactly the same and have the same size offices, regardless of dedication, ability, nature or quality or volume of output and regardless of their race, religion, beauty, shape, fitness, dietary preferences, baldness, hobbies or political views, even if they are Conservatives. All Futurizon offices are safe zones where employees may say anything they want of any level of truth, brilliance or stupidity and expect it to be taken as absolute fact and any consequential emotional needs to be fully met. No employee may criticize any other employee’s mouse mat, desk personalisation or screen wallpaper for obvious lack of taste. All employees are totally free to do anything they choose 100% of the time and can take as much leave as they want. All work is voluntary. All have the same right to respectfully request any other employee to make them coffee, tea or Pimms. All employees of all genders real or imagined are entitled to the same maternity and paternity rights, and the same sickness benefits, whether ill or not. In fact, Futurizon does not discriminate on any grounds whatsoever. We are proud to lead the world in non-discrimination. Unfortunately, our world-leading terms of employment mean that we can no longer afford to hire any new employees.

However, I note that Google has rather more power and influence than Futurizon so their policies count more. They appear (Google also has better lawyers than I can afford, so I must stress that all that follows is my personal opinion) to have firmly decided that diversity is all-important and they seem to want total equality of outcome. The view being expressed not just by Google but by huge swathes of angry protesters seems to be that any difference in workforce representation from that of the general population must arise from discrimination or oppression so must be addressed by positive action to correct it. There are apparently no statistically discernible differences in behavior between genders, or in job or role preference, so any you may have noticed over the time you’ve been alive is just your prejudice. Google says they fully support free speech and diversity of views, but expression of views is apparently only permitted as long as those views are authorized, on penalty of dismissal.

So unless I’m picking up totally the wrong end of the stick here, and I don’t do that often, only 13% of IT engineers are women, but internal policies must ensure that the proportion rises to 50%, whether women want to do that kind of work or not. In fact, nobody may question whether as many women want to work as IT engineers as men; it must now be taken as fact. By extension, since more women currently work in marketing, HR and PR, they must be substituted by men via positive action programs until men fill 50% of those roles. Presumably similar policies must also apply in medical bays for nursing and other staff there, and in construction teams for their nice new buildings. Ditto all other genders, races, religions; all groups must be protected and equalized to USA population proportions, apparently except those that don’t claim to hold sufficiently left-wing views, in which case it is seemingly perfectly acceptable to oppress, ostracize and even expel them.

In other words, freedom of choice and difference in ability, and more importantly freedom from discrimination, must be over-ruled in favor of absolute equality of diversity, regardless of financial or social cost, or impact on product or service quality. Not expressing full and enthusiastic left-wing compliance is seemingly just cause for dismissal.

So, why does this matter outside Google? Well, AI is developing very nicely. In fact, Google is one of the star players in the field right now. It is Google that will essentially decide how much of the AI around us is trained, how it learns, what it learns, what ‘knowledge’ it has of the world. Google will pick the content the AI learns from, and overrule or reeducate it if it draws any ‘wrong’ conclusions about the world, such as that more women than men want to be nurses or work in HR, or that more men than women want to be builders or engineers. A Google AI must presumably believe that the only differences between men and women are physical, unless their AI is deliberately excluded from the loudly declared corporate values and belief sets.

You should be very worried. Google’s values really matter. They have lots of influence on some of the basic tools of everyday life. Even outside their company, their AI tools and approaches will have strong influence on how other AI develops, determining operating systems and platforms, languages, mechanisms, interfaces, filters, even prejudices and that reach and influence is likely to increase. Their AI may well be in many self-driving cars, and if they have to make life or death decisions, the underlying value assumptions must feature in the algorithms. Soon companies will need AI that is more emotionally compliant. AI will use compliments or teasing or seduction or sarcasm or wit as marketing tools as well as just search engine positioning. Soon AI will use highly expressive faces with attractive voices, with attractive messages, tailored to appeal to you by pandering to your tastes and prejudices while thinking something altogether different. AI might be the person at the party that is all smiles and compliments, before going off to tell everyone else how awful it thinks you are. If you dare to say something not ‘authorized’, the ultra-smart AI all around you might treat you condescendingly, making you feel ashamed, ostracized, a dinosaur. Then it might secretly push you down a few pages in search results, or put a negative spin on text summaries about you, or exclude you from recommendations. Or it might do all the secret stuff while pretending it thinks you’re fantastic. Internal cultural policies in companies like Google today could soon be external social engineering to push the left-wing world the IT industry believes in – it isn’t just Google; Facebook and Twitter are also important and just as Left, though Amazon, Samsung, IBM and other AI players are less overtly politically biased, so far at least. Left wing policies generally cost a lot more, but Google and Facebook will presumably still expect other companies and people to pay the taxes to pay for it all. As their female staff gear up to fight them over pay differences between men and women for similar jobs, it often seems that Google’s holier-than-thou morality doesn’t quite make it as far as their finances.

Then it really starts being fun. We’ll soon have bacteria that can fabricate electronic circuits within themselves. Soon they’ll be able to power them too, giving the concept of smart yogurt. These bacteria could also have nanotechnology flagella to help them get around. We’ll soon have bacterial spies all over our environment, even on our skin, intercepting electronic signals that give away our thoughts. They’ll bring in data on everything that is said, everything that everyone even thinks or feels. Those bacteria will be directly connected into AI, in fact they’ll be part of it. They’ll be able to change things, to favor or punish according to whether they like what someone believes in or how they behave.

It isn’t just right-wing extremists that need to worry. I’m apparently Noveau Left – I score slightly left of center on political profiling tests, but I’m worried. A lot of this PC stuff seems extreme to me, sometimes just nonsense. Maybe it is, or maybe I should be lefter. But it’s not my choice. I don’t make the rules. Companies like Google make the rules, they even run the AI ethics groups. They decide much of what people see online, and even the meaning of the words. It’s very 1984-ish.

The trouble with the ‘echo chambers’ we heard about is that they soon normalize views to the loudest voices in those groups, and they don’t tend to be the moderates. We can expect it will go further to the extreme, not less. You probably aren’t left enough either. You should also be worried.

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I D Pearson BSc DSc(hc) FWAAS CITP FBCS FWIF

About me

I’m an all-round futurist/futurologist with a sound engineering foundation and over 1800 inventions. I spend most of my time writing futures material for white papers or to accompany PR campaigns, but I’ve also delivered well over 1000 conference presentations and appeared over 750 times on TV and Radio, often following writing I’ve done for PR campaigns. I’ve written hundreds of commissioned reports, press articles and seven books, most recently Society Tomorrow, Space Anchor, Total Sustainability and You Tomorrow (2nd Edn). I sometimes undertake phone or face-to-face consultancy on any aspect of the future, usually from a technology perspective, using over 30 years experience as a futurologist and engineer. I have demonstrated about 85% accuracy when looking 10-15 years ahead.

I am a Chartered Fellow of the British Computer Society and a Fellow of the World Academy for Arts and Science and the World Innovation Foundation.